Mapping Bronze Disease Onset by Multispectral Reflectography

The early detection of bronze disease is a significant challenge not only in conservation science but also in various industrial fields that utilize copper alloys (i.e., shipbuilding and construction). Due to the aggressive nature of this corrosion pathway, developing methods for its early detection is pivotal. The presence of copper trihydroxychlorides is the main key indicator of the ongoing autocatalytic process. Commonly used for pigment identification, reflectance imaging spectroscopy (RIS) or fiber optics reflectance spectroscopy (FORS) was recently employed for mapping atacamite distribution in extended bronze corrosion patinas. In this work, we detected the onset of bronze disease using visible–near-infrared (VIS-NIR) multispectral reflectography, which allowed for disclosing features that were poorly detectable to the naked eye. The image cube was analyzed using the spectral correlation mapper (SCM) algorithm to map the distribution of copper trihydroxychlorides. FORS and Raman spectroscopy were employed to characterize the patina composition and validate RIS data. A set of bronze samples, representative of Florentine Renaissance workshops, was specifically realized for the present study and artificially aged at different corrosion stages.